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| Nelineárny autoregresný distribuovaný lag (NARDL) model× | Regresia metódou najmenších štvorcov (OLS)× | |
|---|---|---|
| Odbor | Ekonometria | Ekonometria |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 2014 | 2019 |
| Tvorca≠ | Shin, Yu & Greenwood-Nimmo | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Asymmetric cointegration / error-correction model | Linear regression |
| Pôvodný zdroj≠ | Shin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In: Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt. Springer. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Ďalšie názvy≠ | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Príbuzné≠ | 4 | 5 |
| Zhrnutie≠ | The NARDL model, introduced by Shin, Yu and Greenwood-Nimmo in 2014, extends the ARDL framework to capture asymmetric long-run and short-run relationships, testing whether positive and negative changes in a regressor affect the dependent variable differently. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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